Liu Yafang, Zhou Jianlin, Zeng An, Fan Ying, Di Zengru
School of Systems Science, Beijing Normal University, Beijing 100875, People's Republic of China.
Chaos. 2024 Sep 1;34(9). doi: 10.1063/5.0218981.
Link prediction has a wide range of applications in the study of complex networks, and the current research on link prediction based on single-layer networks has achieved fruitful results, while link prediction methods for multilayer networks have to be further developed. Existing research on link prediction for multilayer networks mainly focuses on multiplexed networks with homogeneous nodes and heterogeneous edges, while there are relatively few studies on general multilayer networks with heterogeneous nodes and edges. In this context, this paper proposes a method for heterogeneous multilayer networks based on motifs for link prediction. The method considers not only the effect of heterogeneity of edges on network links but also the effect of heterogeneous and homogeneous nodes on the existence of links between nodes. In addition, we use the role function of nodes to measure the contribution of nodes to form the motifs with links in different layers of the network, thus enabling the prediction of intra- and inter-layer links on heterogeneous multilayer networks. Finally, we apply the method to several empirical networks and find that our method has better link prediction performance than several other link prediction methods on multilayer networks.
链接预测在复杂网络研究中有着广泛的应用，目前基于单层网络的链接预测研究已取得丰硕成果，而多层网络的链接预测方法还有待进一步发展。现有关于多层网络链接预测的研究主要集中在节点同质且边异质的复用网络上，而对于节点和边都异质的一般多层网络的研究相对较少。在此背景下，本文提出一种基于基序的异质多层网络链接预测方法。该方法不仅考虑了边的异质性对网络链接的影响，还考虑了异质和同质节点对节点间链接存在的影响。此外，我们利用节点的角色函数来衡量节点对形成网络不同层中带链接基序的贡献，从而实现对异质多层网络层内和层间链接的预测。最后，我们将该方法应用于几个实证网络，发现我们的方法在多层网络上的链接预测性能优于其他几种链接预测方法。
